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Dynamic Nonlinear Inverse-Model Based Control of a Twin Rotor System Using Adaptive Neuro-fuzzy Inference System

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2 Author(s)
Toha, S.F. ; Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, Sheffield, UK ; Tokhi, M.O.

A dynamic control system design has been a great demand in the control engineering community, with many applications particularly in the field of flight control. This paper presents investigations into the development of a dynamic nonlinear inverse-model based control of a twin rotor multi-input multi-output system (TRMS). The TRMS is an aerodynamic test rig representing the control challenges of modern air vehicle. A model inversion control with the developed adaptive model is applied to the system. An adaptive neuro-fuzzy inference system (ANFIS) is augmented with the control system to improve the control response. To demonstrate the applicability of the methods, a simulated hovering motion of the TRMS, derived from experimental data is considered in order to evaluate the tracking properties and robustness capacities of the inverse- model control technique.

Published in:

Computer Modeling and Simulation, 2009. EMS '09. Third UKSim European Symposium on

Date of Conference:

25-27 Nov. 2009